ElectionShield: A Real-Time AI Framework for Detecting Coordinated Narrative Manipulation During Elections

This paper presents ElectionShield Live, a real-time frame-work for identifying semantically adaptive, emotionally ma-nipulative, and behaviorally coordinated election narratives. By combining narrative classification, emotion scoring, seman-tic clustering, coordination detection, and dashboard visualiza-tion, the system moves beyond isolated fake-news prediction toward campaign-level monitoring. Results indicate strong performance across the main tasks, including 91.4% misinformation classification accuracy, 0.887 clustering F1, 0.901 weighted emotion F1, and 88.2% co-ordination detection accuracy, while maintaining near-real-time response. So, the framework keeps the paper’s main technology more usable form.

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